Function Im2col

tensorflow/lite/kernels/internal/optimized/im2col_utils.h:198–230

template <typename T>
void Im2col(const ConvParams& params, int kheight, int kwidth, uint8 zero_byte,
            const RuntimeShape& input_shape, const T* input_data,
            const RuntimeShape& output_shape, T* output_data) {
  gemmlowp::ScopedProfilingLabel label("Im2col");
  const int stride_width = params.stride_width;
  const int stride_height = params.stride_height;
  const int pad_width = params.padding_values.width;
  const int pad_height = params.padding_values.height;
  TFLITE_DCHECK_EQ(input_shape.DimensionsCount(), 4);
  TFLITE_DCHECK_EQ(output_shape.DimensionsCount(), 4);

  const int batches = MatchingDim(input_shape, 0, output_shape, 0);
  const int input_depth = input_shape.Dims(3);
  const int input_width = input_shape.Dims(2);
  const int input_height = input_shape.Dims(1);
  const int output_depth = output_shape.Dims(3);
  const int output_width = output_shape.Dims(2);
  const int output_height = output_shape.Dims(1);

  int buffer_id = 0;
  // Loop over the output nodes.
  for (int b = 0; b < batches; ++b) {
    for (int h = 0; h < output_height; ++h) {
      for (int w = 0; w < output_width; ++w) {
        ExtractPatchIntoBufferColumn(
            input_shape, w, h, b, kheight, kwidth, stride_width, stride_height,
            pad_width, pad_height, input_width, input_height, input_depth,
            output_depth, buffer_id, input_data, output_data, zero_byte);
        ++buffer_id;
      }
    }
  }
}

}  // namespace optimized_ops
}  // namespace tflite